本文整理汇总了Python中data_utils.test_set方法的典型用法代码示例。如果您正苦于以下问题：Python data_utils.test_set方法的具体用法？Python data_utils.test_set怎么用？Python data_utils.test_set使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类data_utils的用法示例。
在下文中一共展示了data_utils.test_set方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: evaluate
# 需要导入模块: import data_utils [as 别名]
# 或者: from data_utils import test_set [as 别名]
def evaluate():
"""Evaluate an existing model."""
batch_size = FLAGS.batch_size
tasks = FLAGS.task.split("-")
with tf.Session() as sess:
model, min_length, max_length, _, _, ensemble = initialize(sess)
bound = data.bins[-1] + 1
for t in tasks:
l = min_length
while l < max_length + EXTRA_EVAL and l < bound:
_, seq_err, _ = single_test(l, model, sess, t, FLAGS.nprint,
batch_size, ensemble=ensemble)
l += 1
while l < bound + 1 and not data.test_set[t][l]:
l += 1
# Animate.
if FLAGS.animate:
anim_size = 2
_, _, test_data = single_test(l, model, sess, t, 0, anim_size,
get_steps=True)
animate(l, test_data, anim_size)
# More tests.
_, seq_err = multi_test(data.forward_max, model, sess, t, FLAGS.nprint,
batch_size * 4, ensemble=ensemble)
if seq_err < 0.01: # Super-test if we're very good and in large-test mode.
if data.forward_max > 4000 and len(tasks) == 1:
multi_test(data.forward_max, model, sess, tasks[0], FLAGS.nprint,
batch_size * 64, 0, ensemble=ensemble)